support different Pinecone initialization depending on the version

llama_index/vector_stores/pinecone.py

@@ -10,6 +10,9 @@
 from functools import partial
 from typing import Any, Callable, Dict, List, Optional, cast
 
+from packaging import version
+from pkg_resources import get_distribution
+
 from llama_index.bridge.pydantic import PrivateAttr
 from llama_index.schema import BaseNode, MetadataMode, TextNode
 from llama_index.vector_stores.types import (
@@ -69,7 +72,8 @@ def _transform_pinecone_filter_operator(operator: str) -> str:
 
 
 def build_dict(input_batch: List[List[int]]) -> List[Dict[str, Any]]:
-    """Build a list of sparse dictionaries from a batch of input_ids.
+    """
+    Build a list of sparse dictionaries from a batch of input_ids.
 
     NOTE: taken from https://www.pinecone.io/learn/hybrid-search-intro/.
 
@@ -93,7 +97,8 @@ def build_dict(input_batch: List[List[int]]) -> List[Dict[str, Any]]:
 def generate_sparse_vectors(
     context_batch: List[str], tokenizer: Callable
 ) -> List[Dict[str, Any]]:
-    """Generate sparse vectors from a batch of contexts.
+    """
+    Generate sparse vectors from a batch of contexts.
 
     NOTE: taken from https://www.pinecone.io/learn/hybrid-search-intro/.
 
@@ -105,7 +110,8 @@ def generate_sparse_vectors(
 
 
 def get_default_tokenizer() -> Callable:
-    """Get default tokenizer.
+    """
+    Get default tokenizer.
 
     NOTE: taken from https://www.pinecone.io/learn/hybrid-search-intro/.
 
@@ -157,7 +163,8 @@ def _to_pinecone_filter(standard_filters: MetadataFilters) -> dict:
 
 
 class PineconeVectorStore(BasePydanticVectorStore):
-    """Pinecone Vector Store.
+    """
+    Pinecone Vector Store.
 
     In this vector store, embeddings and docs are stored within a
     Pinecone index.
@@ -217,14 +224,24 @@ def __init__(
         if pinecone_index is not None:
             self._pinecone_index = cast(pinecone.Index, pinecone_index)
         else:
-            if index_name is None or environment is None:
-                raise ValueError(
-                    "Must specify index_name and environment "
-                    "if not directly passing in client."
-                )
+            pinecone_client_version = get_distribution("pinecone-client").version
+
+            if version.parse(pinecone_client_version) >= version.parse("3.0.0"):
+                if index_name is None:
+                    raise ValueError(
+                        "Must specify index_name if not directly passing in client."
+                    )
+                pinecone_instance = pinecone.Pinecone(api_key=api_key)
+                self._pinecone_index = pinecone_instance.Index(index_name)
+            else:
+                if index_name is None or environment is None:
+                    raise ValueError(
+                        "Must specify index_name and environment "
+                        "if not directly passing in client."
+                    )
 
-            pinecone.init(api_key=api_key, environment=environment)
-            self._pinecone_index = pinecone.Index(index_name)
+                pinecone.init(api_key=api_key, environment=environment)
+                self._pinecone_index = pinecone.Index(index_name)
 
         insert_kwargs = insert_kwargs or {}
 
@@ -265,8 +282,14 @@ def from_params(
         except ImportError:
             raise ImportError(import_err_msg)
 
-        pinecone.init(api_key=api_key, environment=environment)
-        pinecone_index = pinecone.Index(index_name)
+        pinecone_client_version = get_distribution("pinecone-client").version
+
+        if version.parse(pinecone_client_version) >= version.parse("3.0.0"):
+            pinecone_instance = pinecone.Pinecone(api_key=api_key)
+            pinecone_index = pinecone_instance.Index(index_name)
+        else:
+            pinecone.init(api_key=api_key, environment=environment)
+            pinecone_index = pinecone.Index(index_name)
 
         return cls(
             pinecone_index=pinecone_index,
@@ -286,14 +309,15 @@ def from_params(
 
     @classmethod
     def class_name(cls) -> str:
-        return "PinconeVectorStore"
+        return "PineconeVectorStore"
 
     def add(
         self,
         nodes: List[BaseNode],
         **add_kwargs: Any,
     ) -> List[str]:
-        """Add nodes to index.
+        """
+        Add nodes to index.
 
         Args:
             nodes: List[BaseNode]: list of nodes with embeddings
@@ -353,7 +377,8 @@ def client(self) -> Any:
         return self._pinecone_index
 
     def query(self, query: VectorStoreQuery, **kwargs: Any) -> VectorStoreQueryResult:
-        """Query index for top k most similar nodes.
+        """
+        Query index for top k most similar nodes.
 
         Args:
             query_embedding (List[float]): query embedding